To answer this question I gathered predictions in early November from most popular sites and other googled sources [btw, it’s not a closed list so if you want to add your’s predictions let me know in the comments] and compared them to actual results by Root Mean Square Deviation which is essentially average difference between each prediction and result in terms of absolute value.
If you want to play with numbers or check any single entry just download NBA Predictions Accuracy 2012-13.pdf but if you are interested only in the results they are in the table below…

But please keep in mind two important notes:
1) don’t think or assume it’s all about the skills of people involved because randomness plays a part here… and it’s hard for the better example than Minnesota Timberwolves in 2012-13. Literally everybody thought they would be better this season but they were crushed by injuries and in the end the best prediction for this team turned out to be from… last years’ adjusted wins! So if someone predicted 45 wins for them his result was punished by bad luck more than someone who predicted 35 wins for them.
Well, unless someone can predict injuries…

2) in most cases entries next to each other are basically interchangeable in terms of accuracy because difference between them can be translated into “2-3 more/less wins in the right direction would flip them”.

A couple of notes about the results in the 5th season measured:

– The most undervalued teams were Warriors [by an average of 11.1 wins], Rockets [10.7 – thanks Harden!], Grizzlies [9.1], Nets [6.8], Clippers [6.4], Knicks [6.1] and Heat [6.0]. I guess people underestimated how bad Eastern Conference will be… because teams like Nets, Knicks and Heat on any undervalued list are surprising.

– I have to congratulate John Hollinger on many levels. Not only he won for the second time [after 2010-11] and beat Vegas AGAIN but his fame reached Memphis Grizzlies so they signed him to a deal. I’m sure his main responsibility there will be predicting wins for another season ;-) Unfortunately, we won’t be able to see it.

– last year’s “scouted gem” and “promising prospect” Joe Schaller from rivals.com proved it was not a contract year and became a “respected veteran” in the group. OK, too many clichés in one sentence but congratulations for him are in order.

– wisdom of the crowd in form of ESPN forecast had 5th strong year in a row… and not only they noticed it but also created a NBA ESPN Forecast. I didn’t see that one coming but that’s an interesting twist for me.

– yes, over/under numbers from Vegas were still good.

– last year’s predictions had a surprisingly short list of competitors and I was a little worried about it but fortunately it was an outlier caused by the lockout. Hopefully more of them will continue to do it in future seasons.

– after last year’s strong showing from members of APBR forum this season was clearly a disappointment.
I guess the moral of this story is “you have to participate to win”…

– I didn’t include predictions from Bill Simmons because on his podcast with Joe House for some teams they both only said “over” or “under” without any specific number.

For those interested the theoretical limit on the RMSE is roughly 4.5 in the NBA, for comparison.
Success in predictions in single seasons don’t carry much meaning, a gradual view must be built.
I suggest that predicting total point margin for a season would be a much better test of predictive ability as it contains less random error than wins due to one result being granular and near-continuous whist the other is binary and discontinuous.

The Lakers weren’t misvalued because of injury, they’re roughly a 50 win team at full strength. Age and poor roster construction ensured they’d never be great.
V-zero and thenbamodeller are the same, so you may as well choose one or the other – I don’t need two entries. :P The Twolves were horribly injury prone, completely screwing possibly good predictions, and Asik was undervalued by the market for the Rockets.

Anyway, thanks for all the info – I’ll be back next year @ thenbamodeller blog, to which I’ll also be posting some playoffs stuff soon (ate, obviously) and other devvelopments I have made over the last six months.

“Success in predictions in single seasons don’t carry much meaning, a gradual view must be built”
That’s why I try to collect more and more data. 5 seasons is a nice start and there seems to be some consistency among authors. I just wish more of them did it each year.

“I suggest that predicting total point margin for a season would be a much better test of predictive ability as it contains less random error than wins due to one result being granular and near-continuous whist the other is binary and discontinuous.”
Very true but that would require a change from predictors themselves – they don’t predict margins but wins so even though technically we could translate it I don’t want to put numbers into their mouths.

“V-zero and thenbamodeller are the same, so you may as well choose one or the other – I don’t need two entries. :P”
;-) Thanks for the info. I fixed it and removed entry from “v-zero”.

Wow, I beat Hollinger! That’s awesome! So now it’s just a matter of time before I get a front office job in the NBA, right?

You’ve probably noticed that my blog (http://siganba.blogspot.com) is in Portuguese (and has been inactive for a while). But if I do make predictions for next season, I’ll make sure to let you know. Even if I don’t, I might send you them just for fun.

Yes, I noticed it – the language was probably the reason I didn’t find – and it felt a little weird it was your last post but congratulations anyway. Show everyone next year it wasn’t a fluke ;-) Thanks in advance for sending them.

And we don’t know why exactly Hollinger was hired, maybe it was because of his writing skills ;-)

Yeah, that was the last post I wrote there. Unfortunately, as you can imagine, blogging about basketball does not make you any money in Brazil. I posted daily previews (and actually had some decent traffic) in October, but then I got a new job that takes way too much of my time for me to able to keep the blog updated. I also stopped tweeting (@Siga_NBA) shortly thereafter. I do hope I can find the time to start writing again in the future.

Anyway, I’m pretty sure it WAS a fluke! My predictions weren’t analytics-based at all, so I really don’t think I’ve found a winning formula or anything like that. More than likely, I just got lucky. Still pretty cool, though!

I’m surprised it’s not more terrible considering I didn’t put too much work into them and I was destroyed in the west (Lakers, of course, but Curry was healthy all year, Denver was better than I thought, and Phoenix and New Orleans threw me off — Nash leaving probably killed morale and Ryan Anderson slumped a little, while Anthony Davis despite nice stats didn’t have a good impact.) My RMSE in the west was 8.90 and in the east 6.35.

Also, for Wins Produced, were you using their decimal predictions or did you round up? I think a prediction of 57.14 wins is pretty stupid and goes against what we’re doing. I calculated the rounded forms for WOW1 at 7.71 and WOW2 at 7.91.

I double-checked and I have the same result for your predictions. Thanks for the link.

“Also, for Wins Produced, were you using their decimal predictions or did you round up?”
I used a form in which author published it…

“I calculated the rounded forms for WOW1 at 7.71 and WOW2 at 7.91.”

… but as you can see it doesn’t change much and in this case rounded numbers were worse!!!

“I think a prediction of 57.14 wins is pretty stupid and goes against what we’re doing. ”
Why? It’s like hedging a bet between 57 and 58 wins. Also note that all Vegas’ lines have half-win and it doesn’t affect their accuracy.

The funny thing is Wages of Wins forecasts seem to do considerably worse job than Hollinger.
Surely it would take more than just one season of data to conclude anything of value about their methods, but I guess John has his small win after all.

But is it even a semi-fair comparison of methods? Maybe Hollinger is just better at predicting minutes or injuries… IMHO the more interesting question is how much did Hollinger use PER for his predictions?

To be fair, Wins Produced made positions played matter more than any other tool so you kind of created your own additional problem with inability to predict them.

But overall, there are so many variables at play here that without entire dataset responsible for predictions it’s hard to know what exactly went wrong and where: But you can investigate your own mistakes which I wish more people would do. Hopefully this series will help in some way.

I also have 6.6 for your simple average but in terms of RMSE your score was 8.6.
And Rockets screwed almost everybody so you can easily improve your rank by removing them ;-)
BTW, do you realize your predictions added up to 1245 wins?

I picked the Spurs to beat the Heat one year in advance. I also picked OKC to beat Miami last year (one year in advance). In the last 10 years, I’ve picked at least one of the NBA championship teams correctly one year in advance. I always make my predictions for the upcoming year as soon as the last championship game ends.